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General Social Survey Report

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As seen above, I recoded the General Social Survey 2016 HEALTH variable to R_HEALTH in order to assess if respondents viewed their health as poor, fair, good, and excellent. The original HEALTH variable assessed health in a deteriorating health order, so I recoded it into R_HEALTH with an improving health order. In addition, I recoded the INCOME16 variable into INCOME16_5 by splitting the data into 5 categories. By calculating the medians from each range of values, I was able to simplify the variable and assure that each value was spaced apart by $30,000. In order to assess if income is a statistically significant predictor of perceived health quality, I will conduct both a crosstabulation and a regression.
Additionally, I utilized the variables …show more content…
As respondents have higher household incomes, there are more respondents who assess their health as excellent and good. Additionally, less respondents with higher family incomes assess their health as fair or poor. Since the Pearson’s Chi-Square value of 143.81 is statistically significant, we can reject the null hypothesis and assume that there is too much difference of perceived health conditions among respondents with various family income values to have occurred by chance. Therefore, family income is a statistically significant predictor of perceived health …show more content…
Additionally, the F-change of 61.22 is statistically significant. For every extra $30,000 that a respondent makes in this model, their perceived health quality improves by 0.121 on the health scale. Even though this is slightly less of a change than the first model, every extra year of education that a respondent gets also improves their health by 0.053 on the health scale. Additionally, the F change is statistically significant, which portrays how education is beneficial to the model. Even though the third model does not have a statistically significant F-change, the combination of family income, years of education, and if the respondent is female can account for 10% of the variability in perceived conditions of health. In this model, the slopes for family income and education remain statistically significant and generally similar to model 2. However, if a respondent is female does not have a statistically significant relationship on perceived quality of

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